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This is the data and the code associated to the data-base review paper "Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion" published on Sensors in 2017 doi:10.3390/s17061257 in which we have compared 5 algorithms over a dataset comparing inertial data with Vicon based data.

Contacts:

Content

  1. data from data capture experiment (see Ethical Approval in paper)
  2. code for the analysis

Code

Use Data:

  • UpS4.mat for the calibration
  • UpS10.mat for analysis

Code: starts with MATLAB main.m

Matlab file of IMU+Vicon data

Vicon and IMU data are Time Aligned

Files

Six Sessions with same subject

UpS1.mat UpS4.mat UpS8.mat UpS10.mat UpS12.mat UpS20.mat

Content

Each file contains a struct with:

  • imu sensors (internal names) limbs (names of limbs) labels (of data 62 names)

    Various IMUs: R_Shoulder Pelvis R_lower_arm L_upper_arm ... 63 values: 1 virtual time, and labels

    Content of Data

    'timestamp' 'magx' 'magy' 'magz' 'accx' 'accy' 'accz' 'acc2x' 'acc2y' 'acc2z' 'gyrox' 'gyroy' 'gyroz' 'temperature' 'mix_temp' 'mix_bat' 'joy_volt1' 'joy_volt2' 'joy_button_mask1' 'joy_button_mask2' 'quat_w' 'quat_x' 'quat_y' 'quat_z' 'freq'

  • vic Various Clusters on Body (11): cam_imu L_lower_arm Trunk R_upper_arm R_Shoulder ... The reference frame is ground fixed

    Content of Data (8 each) valid position quaternion xyzw

Base Poses

These N-Pose and T-Pose are stored inside each sessions at the beginning

References

Please cite the following paper if you use the data or code:

Filippeschi, A.; Schmitz, N.; Miezal, M.; Bleser, G.; Ruffaldi, E.; Stricker, D.	
"Survey of Motion Tracking Methods Based on  Inertial Sensors: A Focus on Upper Limb Human Motion".
Sensors 2017, 17, 1257.

The UKF-based method discussed in the review is the following:

Peppoloni, Lorenzo, et al. 
"A novel 7 degrees of freedom model for upper limb kinematic reconstruction based on wearable sensors".
Intelligent Systems and Informatics (SISY), IEEE, 2013.